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B-E in Computer Science And Engineering at AMC Engineering College
Bengaluru, Karnataka
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About the Specialization
What is Computer Science and Engineering at AMC Engineering College Bengaluru?
This Computer Science and Engineering program at AMC Engineering College focuses on equipping students with foundational and advanced knowledge in computing. The curriculum is meticulously designed to meet the evolving demands of the Indian IT industry, emphasizing both theoretical concepts and practical applications. It covers core areas such as programming, data structures, algorithms, operating systems, databases, and networks, preparing graduates for diverse roles in software development, data science, and IT infrastructure management, crucial for India''''s digital economy growth.
Who Should Apply?
This program is ideal for ambitious fresh graduates who have a strong aptitude for problem-solving and logical reasoning, seeking entry into the dynamic field of information technology. It also caters to individuals looking to upskill their technical competencies or career changers aiming to transition into high-demand tech roles. Prerequisites typically include a solid background in Physics, Chemistry, and Mathematics from their 10+2 education, coupled with a keen interest in programming and technology innovation.
Why Choose This Course?
Graduates of this program can expect to secure promising career paths in leading Indian and multinational IT companies, with roles such as Software Developer, Data Analyst, Network Engineer, and Cyber Security Specialist. Entry-level salaries in India typically range from INR 4-7 lakhs per annum, with experienced professionals earning upwards of INR 15-30 lakhs, demonstrating significant growth trajectories. The comprehensive curriculum also aids in preparing for professional certifications in cloud computing, cybersecurity, and data science, enhancing employability.
Student Success Practices
Foundation Stage
Master Core Programming Fundamentals- (Semester 1-2)
Dedicate consistent time to practice programming concepts introduced in subjects like Programming in C and Data Structures. Utilize online coding platforms to solve problems regularly, building a strong base for future advanced topics.
Tools & Resources
HackerRank, LeetCode, GeeksforGeeks, NPTEL courses on C/Python
Career Connection
A strong foundation in programming is essential for cracking technical interviews and excelling in initial software development roles.
Develop Strong Logical and Analytical Skills- (Semester 1-2)
Actively engage with Discrete Mathematics and Engineering Mathematics-I/II by solving a variety of problems. Focus on understanding the logic behind concepts, not just memorization. Participate in college quizzes and logic puzzles.
Tools & Resources
Quantitative Aptitude books, online puzzle websites, competitive math clubs
Career Connection
Critical for algorithm design, debugging, and problem-solving in any engineering or IT role.
Build Interdisciplinary Awareness- (Semester 1-2)
While focusing on core CSE subjects, also pay attention to the fundamental concepts taught in Engineering Physics, Chemistry, and Electrical Engineering. These subjects provide a broader engineering perspective crucial for interdisciplinary projects.
Tools & Resources
Textbooks, YouTube channels for visual learning, cross-departmental workshops
Career Connection
Helps in understanding complex systems, product development, and collaborating with diverse engineering teams in industry.
Intermediate Stage
Dive Deep into Data Structures and Algorithms (DSA)- (Semester 3-4 (intensify in 5))
Beyond coursework, dedicate extra hours to master advanced DSA concepts. Practice implementing different data structures and algorithms in your preferred programming language, participating in coding contests to test your skills.
Tools & Resources
InterviewBit, Codeforces, TopCoder, Cracking the Coding Interview book
Career Connection
DSA proficiency is non-negotiable for placements in product-based companies and highly valued in service companies.
Gain Practical Exposure through Internships and Mini-Projects- (Semester 4-5 (especially after Sem 4))
Actively seek out and complete internships during summer breaks, even unpaid ones, to gain industry experience. Work on multiple mini-projects, applying theoretical knowledge to solve real-world problems and building a portfolio.
Tools & Resources
Internshala, LinkedIn, college placement cell, GitHub for project showcases
Career Connection
Practical experience significantly boosts resume value, provides networking opportunities, and often leads to pre-placement offers.
Build a Strong Foundation in Core Computer Science- (Semester 3-5)
Focus on thoroughly understanding core subjects like Operating Systems, Database Management Systems, and Computer Networks. Implement small components or simulate their functionalities to grasp their working principles in depth.
Tools & Resources
Official documentation, online courses (Coursera, edX), Operating System Concepts by Silberschatz, Database System Concepts by Korth
Career Connection
These core subjects form the backbone of most software systems and are critical for roles in system design, backend development, and cybersecurity.
Advanced Stage
Specialize and Build Advanced Projects- (Semester 6-7 (culminating in Project Work Phase I & II))
Choose professional electives wisely based on your career interests (e.g., AI/ML, Cloud, Cybersecurity). Develop substantial projects in your chosen specialization, collaborating with peers or faculty, aiming for innovative solutions or research papers.
Tools & Resources
Kaggle for datasets, TensorFlow/PyTorch for ML, AWS/Azure/GCP free tiers, research papers
Career Connection
Deep specialization and impactful projects differentiate you, making you highly marketable for specific high-demand roles.
Prepare Systematically for Placements- (Semester 6-8 (intensify from Sem 7))
Start placement preparation early, focusing on aptitude, technical rounds (coding, core CS concepts), and soft skills (communication, group discussions, HR interviews). Attend mock interviews and participate in resume-building workshops.
Tools & Resources
PrepInsta, IndiaBix, Glassdoor for interview experiences, LinkedIn for company research
Career Connection
Well-rounded preparation is key to securing desirable job offers from top companies during campus placements.
Engage in Continuous Learning and Networking- (Semester 6-8 and beyond)
Stay updated with the latest industry trends, technologies, and tools by following tech blogs, attending webinars, and joining professional communities. Network with alumni and industry professionals to explore opportunities and gain insights.
Tools & Resources
Medium, Reddit''''s r/cscareerquestions, LinkedIn, local tech meetups, college alumni network
Career Connection
Lifelong learning and a strong professional network are vital for long-term career growth, mentorship, and discovering new opportunities.
Program Structure and Curriculum
Eligibility:
- Passed 2nd PUC / 12th Std / equivalent exam with English and minimum 45% marks in aggregate in Physics, Chemistry and Mathematics (40% for SC/ST/Category-I). Valid score in entrance exams like CET / COMED-K / JEE.
Duration: 8 semesters (4 years)
Credits: 152 Credits
Assessment: Internal: 50%, External: 50%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 22MAT11 | Engineering Mathematics-I | Core | 4 | Differential Calculus, Integral Calculus, Partial Derivatives, Vector Calculus, Ordinary Differential Equations |
| 22PHY12 | Engineering Physics | Core | 4 | Quantum Mechanics, Lasers and Fiber Optics, Superconductivity, Nanomaterials, Electrical Properties of Materials |
| 22ELE13 | Basic Electrical Engineering | Core | 3 | DC Circuits, AC Circuits, Three-Phase Systems, Electrical Machines, Power Converters |
| 22CIV14 | Elements of Civil Engineering and Mechanics | Core | 3 | Engineering Materials, Concrete Technology, Mechanics of Materials, Structural Analysis, Fluid Mechanics |
| 22EGH15 | English | Core | 2 | Grammar, Communication Skills, Technical Writing, Vocabulary, Public Speaking |
| 22PHYL16 | Engineering Physics Laboratory | Lab | 1 | Measurement techniques, Optical experiments, Electrical experiments, Materials characterization |
| 22BEEL17 | Basic Electrical Engineering Laboratory | Lab | 1 | Verification of theorems, AC/DC circuit analysis, Motor characteristics |
| 22CPL18 | Computer Programming Laboratory | Lab | 1 | C programming basics, Conditional statements, Loops, Functions, Arrays, Strings |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 22MAT21 | Engineering Mathematics-II | Core | 4 | Linear Algebra, Multiple Integrals, Vector Integration, Numerical Methods, Laplace Transforms |
| 22CHE22 | Engineering Chemistry | Core | 4 | Electrochemistry, Corrosion, Water Technology, Fuels and Combustion, Polymer Chemistry |
| 22PCD23 | Programming in C and Data Structures | Core | 3 | C Programming Basics, Pointers and Structures, Data Structures Introduction, Arrays and Linked Lists, Stacks, Queues, Trees |
| 22EGD24 | Engineering Graphics | Core | 3 | Orthographic Projections, Isometric Projections, Sectional Views, Development of Surfaces, Perspective Views |
| 22KVE25 | Kannada (Constitutional / Conversational) | Core | 1 | Basic Kannada grammar, Conversational phrases, Kannada culture, Literature appreciation |
| 22CHEL26 | Engineering Chemistry Laboratory | Lab | 1 | Volumetric analysis, Instrumental methods, Water quality testing, Fuel analysis |
| 22DSLL27 | Data Structures Laboratory | Lab | 1 | Implementation of arrays, Linked lists, Stacks and Queues, Sorting algorithms, Searching algorithms |
| 22EGLL28 | Engineering Graphics and Design Laboratory | Lab | 1 | CAD software for 2D drawings, 3D modeling basics, Orthographic projections in CAD, Isometric views in CAD |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 22CS31 | Discrete Mathematics | Core | 3 | Logic and Proofs, Set Theory and Relations, Functions and Sequences, Graph Theory, Combinatorics and Probability, Algebraic Structures |
| 22CS32 | Data Structures and Applications | Core | 3 | Linear Data Structures (Stacks, Queues, Lists), Non-Linear Data Structures (Trees, Graphs), Hashing Techniques, Searching Algorithms, Sorting Algorithms |
| 22CS33 | Analog and Digital Electronics | Core | 3 | Diodes and Transistors, Operational Amplifiers, Logic Gates and Boolean Algebra, Combinational Logic Circuits, Sequential Logic Circuits (Flip-flops, Counters) |
| 22CS34 | Computer Organization and Architecture | Core | 3 | Basic Computer Structure, Processor Design and Instruction Set, Memory System Hierarchy, Input/Output Organization, Pipelining and Parallel Processing |
| 22CS35 | Object Oriented Programming with Java | Core | 3 | Java Language Fundamentals, Classes, Objects, and Methods, Inheritance and Polymorphism, Interfaces and Packages, Exception Handling and Multithreading |
| 22CSL36 | Data Structures and Analog & Digital Electronics Lab | Lab | 2 | C/Java implementation of Data Structures, Logic Gates and Boolean functions, Combinational circuit design, Sequential circuit design (Flip-flops, Counters) |
| 22CSL37 | Object Oriented Programming with Java Laboratory | Lab | 2 | Java program development, Implementation of OOP concepts, GUI applications with JavaFX/Swing, Exception handling and file I/O, Multithreading applications |
| 22MAT38 | Transforms and Numerical Techniques | Core | 1 | Fourier Series and Transforms, Z-Transforms, Numerical methods for equations, Numerical Integration and Differentiation, Finite Differences |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 22CS41 | Design and Analysis of Algorithms | Core | 3 | Algorithm Design Paradigms, Asymptotic Analysis, Divide and Conquer, Greedy Algorithms and Dynamic Programming, Backtracking and Branch and Bound |
| 22CS42 | Operating Systems | Core | 3 | Operating System Structure, Process Management and CPU Scheduling, Deadlocks and Concurrency, Memory Management and Virtual Memory, File Systems and I/O Systems |
| 22CS43 | Microcontrollers and Embedded Systems | Core | 3 | Microcontroller Architecture (e.g., ARM Cortex), Instruction Set and Programming, Interfacing Peripherals, Embedded C Programming, Real-Time Operating Systems (RTOS) Concepts |
| 22CS44 | Database Management Systems | Core | 3 | Database Concepts and Architecture, ER Model and Relational Model, SQL Query Language, Normalization and Dependencies, Transaction Management and Concurrency Control |
| 22CS45 | Principles of Artificial Intelligence | Core | 3 | Introduction to AI, Problem Solving and Search Algorithms, Knowledge Representation, Logical Reasoning, Machine Learning Basics |
| 22CSL46 | Microcontrollers and Operating Systems Lab | Lab | 2 | Microcontroller programming (ARM Cortex), Peripheral interfacing experiments, OS system calls and process creation, Process synchronization mechanisms, Memory allocation strategies |
| 22CSL47 | Database Management Systems Laboratory | Lab | 2 | SQL queries (DDL, DML, DCL), Database design and ER diagrams, PL/SQL programming, Stored procedures and triggers, Database connectivity (JDBC/ODBC) |
| 22ID48 | Design Thinking | Core | 1 | Introduction to Design Thinking, Empathize and Define phases, Ideation techniques, Prototyping and Testing, User-centered design |
Semester 5
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 22CS51 | Automata Theory and Computability | Core | 3 | Finite Automata and Regular Expressions, Context-Free Grammars and Languages, Pushdown Automata, Turing Machines, Undecidability and Complexity Classes |
| 22CS52 | Computer Networks | Core | 3 | Network Models (OSI, TCP/IP), Physical and Data Link Layer, Network Layer (IP addressing, Routing), Transport Layer (TCP, UDP), Application Layer Protocols (HTTP, DNS, FTP), Network Security Basics |
| 22CS53 | Software Engineering | Core | 3 | Software Process Models, Requirements Engineering, Software Design Concepts, Software Testing Strategies, Software Project Management |
| 22CS54X | Professional Elective-1 (e.g., Cloud Computing) | Elective | 3 | Cloud Architecture and Deployment Models, Virtualization Technology, Cloud Service Models (IaaS, PaaS, SaaS), Cloud Security and Data Privacy, Cloud Computing Platforms (AWS, Azure) |
| 22CS55X | Open Elective-1 (e.g., Python Programming for Engineers) | Elective | 3 | Python Syntax and Data Types, Control Flow and Functions, Object-Oriented Programming in Python, File Handling and Exception Handling, Introduction to Python Libraries (NumPy, Pandas) |
| 22CSL56 | Computer Networks and Software Engineering Lab | Lab | 2 | Network configuration and troubleshooting, Socket programming, Network simulation tools (e.g., Wireshark), Software requirements analysis, Design of software components |
| 22CSL57 | Automata Theory and Computability Laboratory | Lab | 2 | Implementation of Finite Automata, Conversion of NFA to DFA, Regular Expression parsers, Context-Free Grammar parsers, Turing machine simulation |
| 22CS58 | Internship-I / Mini Project | Project | 1 | Project identification and planning, Literature review, System design, Implementation and testing, Report writing and presentation |
Semester 6
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 22CS61 | Compiler Design | Core | 3 | Lexical Analysis and Lexers, Syntax Analysis and Parsers, Semantic Analysis and Type Checking, Intermediate Code Generation, Code Optimization and Code Generation |
| 22CS62 | Web Technologies | Core | 3 | HTML5 and CSS3, JavaScript and DOM Manipulation, XML and AJAX, Server-Side Scripting (e.g., PHP, Node.js), Web Services (REST, SOAP), Web Security Fundamentals |
| 22CS63X | Professional Elective-2 (e.g., Machine Learning) | Elective | 3 | Introduction to Machine Learning, Supervised Learning (Regression, Classification), Unsupervised Learning (Clustering), Neural Networks and Deep Learning Basics, Model Evaluation and Selection |
| 22CS64X | Professional Elective-3 (e.g., Internet of Things) | Elective | 3 | IoT Architecture and Protocols, Sensors, Actuators, and Microcontrollers, Wireless Communication Technologies, IoT Platforms and Cloud Integration, Data Analytics in IoT, IoT Security and Privacy |
| 22CS65X | Open Elective-2 (e.g., Fundamentals of Data Science) | Elective | 3 | Data Collection and Preprocessing, Exploratory Data Analysis, Data Visualization, Basic Statistical Concepts, Introduction to Machine Learning Models |
| 22CSL66 | Compiler Design and Web Technologies Lab | Lab | 2 | Lexical analyzer implementation, Parser development, HTML/CSS/JavaScript web page creation, Dynamic web content with backend integration |
| 22CSEL67 | Professional Elective Lab (e.g., Machine Learning Lab) | Lab | 2 | Implementation of regression algorithms, Implementation of classification algorithms, Clustering techniques using Python libraries, Data preprocessing and feature engineering, Model evaluation and hyperparameter tuning |
| 22CS68 | Professional Practice | Core | 1 | Technical communication skills, Professional ethics and conduct, Group discussion techniques, Resume building and interview preparation, Intellectual Property Rights |
Semester 7
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 22CS71 | Artificial Intelligence and Machine Learning | Core | 3 | Advanced AI concepts, Neural Networks and Deep Learning Architectures, Reinforcement Learning, Computer Vision, Natural Language Processing Fundamentals |
| 22CS72X | Professional Elective-4 (e.g., Data Mining) | Elective | 3 | Data Preprocessing and Data Warehousing, Association Rule Mining, Classification Algorithms, Clustering Algorithms, Web Mining and Text Mining |
| 22CS73X | Professional Elective-5 (e.g., DevOps) | Elective | 3 | Introduction to DevOps Principles, Version Control (Git), Continuous Integration/Continuous Delivery (CI/CD), Containerization (Docker), Orchestration (Kubernetes), Infrastructure as Code |
| 22CS74X | Open Elective-3 (e.g., Environmental Science and Engineering) | Elective | 3 | Ecosystems and Biodiversity, Environmental Pollution and Control, Solid Waste Management, Climate Change and Renewable Energy, Environmental Impact Assessment |
| 22CSL75 | Project Work Phase – I | Project | 4 | Problem identification and definition, Extensive literature survey, System design and architecture, Methodology and initial implementation, Interim report preparation |
| 22CS76 | Internship - II (300 Hrs) | Internship | 2 | Industry work exposure, Application of theoretical knowledge, Professional communication, Teamwork and collaboration, Internship report submission |
Semester 8
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| 22CS81X | Professional Elective-6 (e.g., Big Data Engineering) | Elective | 3 | Introduction to Big Data, Hadoop Ecosystem (HDFS, MapReduce), Spark for Big Data Processing, NoSQL Databases (Cassandra, MongoDB), Data Warehousing and ETL Processes, Data Pipelines and Streaming Data |
| 22CS82 | Project Work Phase – II | Project | 6 | Advanced system implementation, Thorough testing and debugging, Performance evaluation and optimization, Project demonstration and viva-voce, Final project report and documentation |
| 22CS83 | Technical Seminar | Core | 1 | Research methodology and literature review, Technical paper presentation skills, Abstract writing and report preparation, Q&A handling and audience engagement, Emerging technologies research |
| 22CS84 | Internship - III (300 Hrs) / Industrial Training | Internship | 2 | Advanced industry project contribution, Specialized skill development, Mentorship and professional networking, Corporate work environment adaptation, Comprehensive internship report |
